Technical Field
[0001] The present invention relates to image synthesizing apparatus and method, position
detecting apparatus and method, and a supply medium, particularly to image synthesizing
apparatus and method, position detecting apparatus and method, and a supply medium
for making it possible that the projected image of a predetermined object seems to
be natural in continuous photographic images by synthesizing the projected image of
the predetermined object with a plurality of continuous photographic images.
Background Art
[0002] Because the computer graphics (CG) art has been advanced in recent years, it is possible
to form a real image almost same as an actually photographed image (taken on the spot)
though the real image is artificially formed. In this case, the processing is frequently
performed in which a predetermined object is continuously photographed (as a dynamic
image) by a video camera and then, the CG image of the predetermined object is synthesized
every image taken on the spot.
[0003] Figure 1 shows a conventional image synthesizing method. In this case, it is assumed
that an existent plate 1 is picked up by an image pickup section 2 and balls 5 and
6 formed through CG are synthesized with the image of the plate 1 so that the balls
5 and 6 seem to be stationary. In this case, the plate 1 on which patterns are drawn
is first actually picked up by an image pickup section 2. In this case, the i-th pattern
formed on the plate 1 is assumed as ai. In this case, symbol i denotes an integer
and also an identification number attached to each pattern ai. The patterns ai are
different from each other in color and shape and therefore, they can be distinguished
between them. The image pickup section 2 uses a stereophonic video camera constituted
with a main video camera and a sub-video camera and is constituted so that three-dimensional
information can be obtained from the parallax between an image picked up by the main
video camera and an image picked up by the sub-video camera. The plate 1 is picked
up while moving the image pickup section 2.
[0004] In this case, the time for the image pickup section 2 to start pickup is assumed
as a first time and a predetermined time after the first time in the pickup time is
assumed as a second time. Figure 1 shows the image pickup section 2 at the first time
and the second time.
[0005] As shown in Figure 2, a frame image 1A
1 obtained by picking up the plate 1 from a predetermined angle is obtained from the
image pickup section 2 at the first time. Similarly, as shown in Figure 3, a frame
image 1A
2 different from the frame image 1A
1 obtained at the first time is obtained at the second time.
[0006] Then, as shown in Figure 4, projected images 5A
1 and 6B
1 of the balls 5 and 6 are synthesized with the image (image in Figure 18) 1A
1 picked up by the image pickup section 2 at the first time. Then, as shown in Figure
5, projected images 5A
2 and 6B
2 of the balls 5 and 6 are synthesized with the image (image in Figure 19) 1A
2 picked up by the image pickup section 2 at the second time at positions where the
balls 5 and 6 seem to be stationary on the plate 1.
[0007] In this case, a method of synthesizing the balls 5 and 6 formed through CG so that
they seem to be stationary on the plate 1 is described below by referring to Figures
6 and 7.
[0008] Though positions for finally synthesizing projected images 5A and 6B are on the two-dimensional
images 1A
1 and 1A
2, the synthesis positions are easily understood by considering them in a three-dimensional
space. Therefore, three-dimensional data (coordinates) is restored from a two-dimensional
frame image. Because the frame image is obtained by the stereophonic video camera,
the above restoration is realized.
[0009] That is, as shown in Figure 6, three-dimensional coordinates are assumed in which
the position of the image pickup section 2 at the first time is an origin O1 and the
horizontal, vertical, and depth directions of the image pickup section 2 are X-axis,
Y-axis, and Z-axis. Then, the three-dimensional position (X1i, Y1i, Z1i) of every
pattern ai of the plate 1 is first obtained from the two-dimensional frame image 1A
1. Then, a user designates a three-dimensional position (three-dimensional synthesis
position) (X1A, Y1A, Z1A) on which the ball 5 is put and a three-dimensional position
(three-dimensional synthesis position) (X1B, Y1B, Z1B) on which the ball 6 is put.
[0010] Then, a synthesis position (two-dimensional position) on the image 1A
1 corresponding to a three-dimensional synthesis position is obtained. The two-dimensional
position is obtained as a position obtained through perspective projection transform
of the three-dimensional position. That is, when assuming the focal distance of the
image pickup section 2 as f, the two-dimensional synthesis position of a projected
image 5A
1 on the image 1A
1 at the first time corresponding to the three-dimensional synthesis position (X1A,
Y1A, Z1A) is obtained as (X1A×f/Z1A, Y1A× f/Z1A). Similarly, the two-dimensional synthesis
position of a projected image 6B
1 on the image 1A
1 at the first time corresponding to the three-dimensional synthesis position (X1B,
Y1B, Z1B) is obtained as (X1B×f/Z1B, Y1B×f/Z1B).
[0011] Similarly, as shown in Figure 7, the position of the image pickup section 2 at the
second time is assumed as an origin O2 and the horizontal, vertical, and depth directions
of the image pickup section 2 are assumed as X-axis, Y-axis, and Z-axis. Then, the
three-dimensional position (X2i, Y2i, Z2i) of every pattern ai of the plate 1 is obtained
from the two-dimensional image 1A
2.
[0012] As described above, because the patterns ai on the plate 1 can be distinguished between
them, it is possible to identify that the i-th pattern ai in the first three-dimensional
coordinate system restored from the image 1A
1 at the first time corresponds to which pattern ai in the second three-dimensional
system restored from the image 1A
2 at the second time. Therefore, it is possible to make the coordinates (X1i, Y1i,
Z1i) of the pattern ai at the first time correspond to the coordinates (X2i, Y2i,
Z2i) of the pattern ai at the second time. Because these two coordinate systems view
the same pattern ai from different angles, the second three-dimensional coordinate
system can be obtained by applying predetermined rotational transform (hereafter,
the function of the transform is assumed as R
1) and predetermined rectilinear transform (hereafter, the function of the transform
is assumed as S
1) to the first three-dimensional coordinate system (though the function of the rectilinear
transform is normally shown by T, it is shown by S because T is used as a variable
showing time in this specification). Therefore, the relation shown by the following
Equation is effected for each pattern ai.

[0013] (Though the function of the rectilinear transform is normally shown by T, it is shown
by S because T is used as a variable showing time in this specification.)
[0014] Therefore, the coordinate transform functions R
1 and S
1 can be obtained by substituting (X1i, Y1i, Z1i) and (X2i, Y2i, Z2i) of each pattern
ai for the above Equation.
[0015] However, when restoring the position (three-dimensional coordinates) of the pattern
ai in a three-dimensional space from image data (image data for the images 1A
1 and 1A
2) in a two-dimensional space picked up at a certain time, the restored position includes
any error. Therefore, when using, for example, the first three-dimensional coordinate
system as a criterion, the position of the i-th pattern ai is not exactly present
at (X1i, Y1i, Z1i). Similarly, when using the second three-dimensional coordinate
system as a criterion, the position of the i-th pattern ai is not exactly present
at (X2i, Y2i, Z2i).
[0016] Therefore, values obtained by squaring the magnitude of the three-dimensional vector
(x1, y1, z1) in the following Equation (1) on every pattern ai by the least-squares
method are totalized to obtain the (most-probable) transform functions R
1 and S
1 for minimizing the total.

[0017] By using the transform functions R
1 and S
1 obtained as described above, the three-dimensional position (X2A, Y2A, Z2A) of the
ball 5 at the second time corresponding to the three-dimensional position (X1A, Y1A,
Z1A) of the ball 5 at the first time is obtained by the following Equation (2).

[0018] Similarly, the position (X2B, Y2B, Z2B) of the ball 6 at the second time corresponding
to the three-dimensional position (X1B, Y1B, Z1B) of the ball 6 at the first time
is obtained by the following Equation (3).

[0019] Then, by applying the relation of the perspective projection transform to the three-dimensional
coordinates (X2A, Y2A, Z2A) and (X2B, Y2B, Z2B), the coordinates (X2A × f/Z2A, Y2A×f/Z2A)
of the projected image 5A
2 and the coordinates (X2B×f/Z2B, Y2B×f/Z2B) of the projected image 6B
2 on the two-dimensional image 1A
2 picked up by the image pickup section 2 at the second time are obtained. By synthesizing
the projected images 5A
2 and 6B
2 with the coordinate positions, a synthesized image must be seen so that the balls
5 and 6 are stationary for the plate 1 because the coordinate positions correspond
to the coordinate positions of the projected images 5A
1 and 6B
1.
[0020] The position of the i-th pattern ai and the positions of the balls 5 and 6 at the
first time are shown as (X1i, Y1i, Z1i), (X1A, Y1A, Z1A), and (X1B, Y1B, Z1B) in the
first three-dimensional coordinate system. Moreover, the position of the i-th pattern
ai and the positions of the balls 5 and 6 at the second time are shown as (X2i, Y2i,
Z2i), (X2A, Y2A, Z2A), and (X2B, Y2B, Z2B) in the second three-dimensional coordinate
system. In this case, the relation between the positions of the i-th patterns ai and
the positions of the balls 5 and 6 in these two coordinate systems can be shown by
the following Equations (4), (5), and (6).

[0021] That is, in the case of middle and bottom Equations among the above three Equations,
because the left-side terms are obtained by operations of the right-side terms, the
right and left terms are equal. However, as described above, the transform functions
R
1 and S
1 are obtained by using the least-squares method and therefore, the functions include
errors. As a result, as shown in the top Equation, the three-dimensional coordinates
(obtained from a second image 1A
2) of the pattern ai of the second image 1A
2 do not accurately coincide with the coordinates obtained by applying the transform
functions R
1 and S
1 to the three-dimensional coordinates (X1A, Y1A, Z1A) of a first image 1A
1.
[0022] Therefore, the relation of projected images 5A
1 and 6B
1 to the pattern ai of the first image 1A
1 at the first time is different from the relation of the projected images 5A
2 and 6B
2 to each pattern ai of the second image 1A
2 at the second time. When reproducing this image string, there is a problem that the
balls 5 and 6 seem to be unnatural because the balls 5 and 6 are lifted from the plate
1 on which the patterns ai are drawn.
Disclosure of the Invention
[0023] The present invention is made to solve the above problems and its object is to provide
an image synthesizing apparatus and method and a supply medium for making it possible
that, when synthesizing the projected image of a predetermined object with a plurality
of photographic images, a synthesized image seems to be natural by synthesizing the
projected image of the predetermined object in accordance with a characteristic point
nearby the synthesis position.
[0024] Moreover, it is another object of the present invention to provide position detecting
apparatus and method and a supply medium capable of correctly calculating the positional
relation of a third image to first and second images.
[0025] Furthermore, it is still another object of the present invention to provide image
synthesizing apparatus and method and a supply medium capable of controlling the fluctuation
of a synthesized image by correcting the position of the projected image of a predetermined
object in accordance with a distortion value when synthesizing the projected image
of the object with a plurality of photographic images.
[0026] The image synthesizing apparatus of claim 1 comprises first means for obtaining a
first characteristic point nearby a synthesis position for synthesizing an object
among the characteristic points projected onto a first image, second means for obtaining
first coordinates of a first characteristic point on a three-dimensional coordinate
system corresponding to the first image, third means for obtaining second coordinates
of a second characteristic point corresponding to the first characteristic point on
a three-dimensional coordinate system corresponding to a second image among the characteristic
points projected onto the second image, fourth means for obtaining coordinate transform
functions of the first and second coordinates, fifth means for obtaining third coordinates
on a three-dimensional coordinate system corresponding to the first image at a synthesis
position for synthesizing an object with the first image, sixth means for obtaining
fourth coordinates on a three-dimensional coordinate system corresponding to the second
image by applying the coordinate transform functions to the third coordinates, and
seventh means for synthesizing the projected image of the object at a position corresponding
to the fourth coordinates of the second image.
[0027] The image synthesizing method of claim 8 comprises the first step of obtaining a
first characteristic point nearby a synthesis position for synthesizing an object
among the characteristic points projected onto a first image, the second step of obtaining
first coordinates on the three-dimensional coordinate system of a first characteristic
point corresponding to the first image, the third step of obtaining second coordinates
of a second characteristic point corresponding to the first characteristic point on
a three-dimensional coordinate system corresponding to a second image among the characteristic
points projected onto the second image, the fourth step of obtaining coordinate transform
functions of the first coordinates and the second coordinates, the fifth step of obtaining
third coordinates on a three-dimensional coordinate system corresponding to the first
image at a synthesis position for synthesizing an object with the first image, the
sixth step of obtaining fourth coordinates on a three-dimensional coordinate system
corresponding to the second image by applying the coordinate transform functions to
the third coordinates, and the seventh step of synthesizing the projected image of
an object at a position corresponding to the fourth coordinates of the second image.
[0028] The supply medium of claim 15 provides a computer program used for an image synthesizing
apparatus for synthesizing the projected image of an object with at least first and
second images and comprising the first step of obtaining a first characteristic point
nearby a synthesis position for synthesizing an object among the characteristic points
projected onto the first image, the second step of obtaining first coordinates of
a first characteristic point on a three-dimensional coordinate system corresponding
to the first image, the third step of obtaining second coordinates of a second characteristic
point corresponding to the first characteristic point on a three-dimensional coordinate
system corresponding to the second image among the characteristic points projected
onto the second image, the fourth step of obtaining coordinate transform functions
of the first and second coordinates, the fifth step of obtaining third coordinates
on a three-dimensional coordinate system corresponding to the first image at a synthesis
position for synthesizing an object with the first image, the sixth step of obtaining
fourth coordinates on a three-dimensional coordinate system corresponding to the second
image by applying the coordinate transform functions to the third coordinates, and
the seventh step of synthesizing the projected image of an object at a position corresponding
to the fourth coordinates of the second image.
[0029] The position detecting apparatus of claim 16 comprises first means for obtaining
a first characteristic point nearby an object among the characteristic points projected
onto a first image, second means for obtaining first coordinates of the first characteristic
point on a three-dimensional coordinate system corresponding to the first image, third
means for obtaining second coordinates of a second characteristic point corresponding
to the first characteristic point on a three-dimensional coordinate system corresponding
to the second image among the characteristic points projected onto the second image,
fourth means for obtaining third coordinates of the object on a three-dimensional
coordinate system corresponding to the first image, fifth means for obtaining fourth
coordinates of the object on a three-dimensional coordinate system corresponding to
the second image, sixth means for obtaining coordinate transform functions of the
first and second coordinates, seventh means for obtaining fifth coordinates on a three-dimensional
coordinate system corresponding to the second image by applying the coordinate transform
functions to the third coordinates, and eighth means for detecting the difference
between the fourth coordinates and the fifth coordinates.
[0030] The position detecting method of claim 17 comprises the first step of obtaining a
first characteristic point nearby an object among the characteristic points projected
onto a first image, the second step of obtaining first coordinates of the first characteristic
point on a three-dimensional coordinate system corresponding to the first image, the
third step of obtaining second coordinates of a second characteristic point corresponding
to the first characteristic point on a three-dimensional coordinate system corresponding
to the second image among the characteristic points projected onto the second image,
the fourth step of obtaining third coordinates of the object on a three-dimensional
coordinate system corresponding to the first image, the fifth step of obtaining fourth
coordinates of the object on a three-dimensional coordinate system corresponding to
the second image, the sixth step of obtaining coordinate transform functions of the
first and second coordinates, the seventh step of obtaining fifth coordinates on a
three-dimensional coordinate system corresponding to the second image by applying
the coordinate transform functions to the third coordinates, and the eighth step of
detecting the difference between the fourth and fifth coordinates.
[0031] The supply medium of claim 18 provides a computer program used for a position detecting
apparatus for detecting the positional relation of an object projected onto first
and second images and comprising the first step of obtaining a first characteristic
point nearby the object among the characteristic points projected onto the first image,
the second step of obtaining first coordinates of the first characteristic point on
a three-dimensional coordinate system corresponding to the first image, the third
step of obtaining second coordinates of a second characteristic point corresponding
to the first characteristic point on a three-dimensional coordinate system corresponding
to the second image among the characteristic points projected onto the second image,
the fourth step of obtaining third coordinates of the object on a three-dimensional
coordinate system corresponding to the first image, the fifth step of obtaining fourth
coordinates of the object on a three-dimensional coordinate system corresponding to
the second image, the sixth step of obtaining coordinate transform functions of the
first and second coordinates, the seventh step of obtaining fifth coordinates on a
three-dimensional coordinate system corresponding to the second image by applying
the coordinate transform functions to the third coordinates, and the eighth step of
detecting the difference between the fourth and fifth coordinates.
[0032] The image synthesizing apparatus of claim 19 comprises image-pickup-device-position
computing means for computing the most-probable position of an image pickup device
when photographing each of a plurality of photographic images, characteristic point
position computing means for computing the most-probable position of the characteristic
point of a first object, virtual projected position computing means for computing
a virtual projected position to which the most-probable position of a characteristic
point is projected when performing photography by using an image pickup device present
at the most-probable position, distortion value computing means for computing a distortion
value in accordance with the difference between a virtual projected position and the
position of a projected image of a characteristic point actually photographed on each
of a plurality of photographic images, correcting means for correcting a position
to which the projected image of a second object is set in accordance with the distortion
value computed by the distortion value computing means, projected image computing
means for computing the projected image of the second object when photographing the
second object from an image pickup device at the most-probable position by assuming
that the second object is located at the corrected position by the correcting means,
and synthesizing means for synthesizing the projected image of the second object computed
by the projected image computing means with each photographic image.
[0033] The image synthesizing method of claim 21 comprises the image-pickup-device-position
computing step of computing the most-probable position of an image pickup device when
photographing each of a plurality of photographic images, the characteristic point
position computing step of computing the most-probable position of the characteristic
point of a first object, the virtual projected position computing step of computing
a virtual projected position to which the most-probable position of a characteristic
point is projected when performing photography by using an image pickup device present
at the most-probable position, distortion value computing step of computing a distortion
value in accordance with the difference between a virtual projected position and the
position of the projected image of a characteristic point actually photographed on
each of a plurality of photographic images, the correcting step of correcting a position
to which the projected image of a second object is set in accordance with the distortion
value computed in the distortion value computing step, the projected image computing
step of computing the projected image of the second object when photographing the
second object from an image pickup device at the most-probable position by assuming
that the second object is located at the position corrected in the correcting step,
and the synthesizing step of synthesizing the projected image of the second object
computed in the projected image computing step with each photographic image.
[0034] The supply medium of claim 23 provides a computer program used for an image synthesizing
apparatus for synthesizing the projected image of a second object with each of a plurality
of photographic images on which a first object photographed by an image pickup device
is photographed by assuming that the second object is located at a predetermined position
and comprising the image-pickup-device-position computing step of computing the most-probable
position of the image pickup device when photographing each of a plurality of photographic
images, the characteristic point position computing step of computing the most-probable
position of the characteristic point of the first object, virtual projected position
computing step of computing a virtual projected position to which the most-probable
position of a characteristic point is projected when performing photography by using
an image pickup device present at the most-probable position, the distortion value
computing step of computing a distortion value in accordance with the difference between
a virtual projected position and the position of the projected image of the characteristic
point actually photographed on each of a plurality of photographic images, the correcting
step of correcting a position to which the projected image of a second object is set
in accordance with the distortion value computed in the distortion value computing
step, projected image computing step of computing the projected image of the second
object when photographing the second object from an image pickup device at the most-probable
position by assuming that the second object is located at the position corrected in
the correcting step, and the synthesizing step of synthesizing the projected image
of the second object computed in the projected image computing step with each photographic
image.
[0035] In the case of the image synthesizing apparatus of claim 1, first means obtains a
first characteristic point nearby a synthesis position for synthesizing the image
of an object among the characteristic points projected onto a first image, second
means obtains first coordinates of a first characteristic point on a three-dimensional
coordinate system corresponding to the first image, third means obtains second coordinates
of a second characteristic point corresponding to the first characteristic point on
a three-dimensional coordinate system corresponding to a second image among the characteristic
points projected onto the second image, fourth means obtains coordinate transform
functions of the first and second coordinates, fifth means obtains third coordinates
on a three-dimensional coordinate system corresponding to the first image at a synthesis
position for synthesizing the object with the first image, sixth means obtains fourth
coordinates on a three-dimensional coordinate system corresponding to the second image
by applying the coordinate transform functions to the third coordinates, and seventh
means synthesizes the projected image of the object at a position corresponding to
the fourth coordinates of the second image.
[0036] In the case of the image synthesizing method of claim 8 and the supply medium of
claim 15, a first characteristic point nearby a synthesis position for synthesizing
an object is obtained among the characteristic points projected onto a first image,
first coordinates of the first characteristic point on a three-dimensional coordinate
system corresponding to the first image are obtained, second coordinates of a second
characteristic point corresponding to the first characteristic point on a three-dimensional
coordinate system corresponding to the second image among the characteristic points
projected onto the second image are obtained, coordinate transform functions of the
first and second coordinates are obtained, third coordinates on a three-dimensional
coordinate system corresponding to the first image at a synthesis position for synthesizing
the object with the first image are obtained, and fourth coordinates on a three-dimensional
coordinate system corresponding to the second image are obtained by applying the coordinate
transform functions to the third coordinates to synthesize the projected image of
the object at a position corresponding to the fourth coordinates of the second image.
[0037] In the case of the position detecting apparatus of claim 16, first means obtains
a first characteristic point nearby an object among the characteristic points projected
onto a first image, second means obtains first coordinates of the first characteristic
point on a three-dimensional coordinate system corresponding to the first image, third
means obtains second coordinates of a second characteristic point corresponding to
the first characteristic point on a three-dimensional coordinate system corresponding
to the second image among the characteristic points projected onto the second image,
fourth means obtains third coordinates of the object on a three-dimensional coordinate
system corresponding to the first image, fifth means obtains fourth coordinates of
the object on a three-dimensional coordinate system corresponding to the second image,
sixth means obtains coordinate transform functions of the first and second coordinates,
seventh means obtains fifth coordinates on a three-dimensional coordinate system corresponding
to the second image by applying the coordinate transform functions to the third coordinates,
and eighth means detects the difference between the fourth and fifth coordinates.
[0038] In the case of the position detecting method of claim 17 and the supply medium of
claim 18, a first characteristic point nearby an object is obtained among the characteristic
points projected onto a first image, first coordinates of the first characteristic
point on a three-dimensional coordinate system corresponding to the first image are
obtained, second coordinates of a second characteristic point corresponding to the
first characteristic point on a three-dimensional coordinate system corresponding
to the second image are obtained among the characteristic points projected onto the
second image, third coordinates of the object on a three-dimensional coordinate system
corresponding to the first image are obtained, fourth coordinates of the object on
a three-dimensional coordinate system corresponding to the second image are obtained,
coordinate transform functions of the first and second coordinates are obtained, and
fifth coordinates on a three-dimensional coordinate system corresponding to the second
image are obtained by applying the coordinate transform functions to the third coordinates
to detect the difference between the fourth and fifth coordinates.
[0039] In the case of the image synthesizing apparatus of claim 19, image-pickup-device-position
computing means computes the most-probable position of an image pickup device when
photographing each of a plurality of photographic images, characteristic point position
computing means computes the most-probable position of the characteristic point of
a first object, virtual projected position computing means computes a virtual projected
position to which the most-probable position of a characteristic point is projected
when performing photography by using an image pickup device present at the most-probable
position, distortion value computing means computes a distortion value in accordance
with the difference between a virtual projected position and the position of the projected
image of the characteristic point actually photographed on each of a plurality of
photographic images, correcting means corrects a position to which the projected image
of a second object is set in accordance with the distortion value computed by the
distortion value computing means, projected image computing means computes the projected
image of the second object when photographing the second object from an image pickup
device present at the most-probable position by assuming that a second object is located
at the position corrected by the correcting means, and synthesizing means synthesizes
the projected image of the second object computed by the projected image computing
means with each photographic image.
[0040] In the case of the image synthesizing method of claim 21 and the supply medium of
claim 23, the most-probable position of an image pickup device when photographing
each of a plurality of photographic images is computed, the most-probable position
of a characteristic point of a first object is computed, a virtual projected position
to which the most-probable position of a characteristic point is projected when performing
photography by using an image pickup device set to the most-probable position is computed,
a distortion value is computed in accordance with the difference between a virtual
projected position and the position of the projected image of the characteristic point
actually photographed on each of a plurality of photographic images, a position to
which the projected image of a second object is set in accordance with the computed
distortion value is corrected, and the projected image of the second object when photographing
the second object from an image pickup device present at the most-probable position
is computed by assuming that the second object is located at a corrected position
to synthesize the projected image of the computed second object with each photographic
image.
BRIEF DESCRIPTION OF THE DRAWINGS
[0041]
Figure 1 is an illustration showing a positional relation between the image pickup
section 2 and the plate 1 of a conventional image synthesizing method;
Figure 2 is an illustration showing an image pickup example of the plate 1 of the
image pickup section 2 in Figure 1;
Figure 3 is an illustration of another image pickup example of the plate 1 of the
image pickup section 2 in Figure 1;
Figure 4 is an illustration showing a synthesizing example of the balls 5 and 6 in
Figure 1;
Figure 5 is an illustration showing another synthesizing example of the balls 5 and
6 in Figure 1;
Figure 6 is an illustration showing a positional relation between the image pickup
section 2 and the plate 1 in Figure 1;
Figure 7 is an illustration showing another positional relation between the image
pickup section 2 and the plate 1 in Figure 1;
Figure 8 is a block diagram showing the structure of the first embodiment of an image
synthesizing apparatus of the present invention;
Figure 9 is a flowchart for explaining an operation of the embodiment in Figure 8;
Figure 10 is an illustration showing a positional relation between the image pickup
section 2 and the plate 1 of the embodiment in Figure 8;
Figure 11 is an illustration showing another positional relation between the image
pickup section 2 and the plate 1 of the embodiment in Figure 8;
Figure 12 is a flowchart for explaining another operation of the embodiment in Figure
8;
Figure 13 is an illustration showing a positional relation between the image pickup
section 2 and the plate 1 of the embodiment in Figure 8;
Figure 14 is an illustration showing another positional relation between the image
pickup section 2 and the plate 1 of the embodiment in Figure 8;
Figure 15 is an illustration for explaining a relation between an image pickup device
and a world coordinate system;
Figure 16 is an illustration for explaining the projected image of a point based on
world coordinates;
Figure 17 is a block diagram showing the structure of the second embodiment of an
image synthesizing apparatus of the present invention;
Figure 18 is a flowchart for explaining an operation of the embodiment in Figure 17;
Figure 19 is an illustration for explaining the processing for picking up an object
with an image pickup device;
Figure 20 is an illustration showing an example of synthesizing a CG image with an
actually picked-up image;
Figure 21 is an illustration for explaining the change of an actually picked-up image;
Figure 22 is an illustration for explaining the change of CG images; and
Figure 23 is an illustration for explaining the change of a synthesized image of a
picked-up image with a CG image.
Best Mode for Carrying Out the Invention
[0042] An embodiment of the present invention is described below by referring to the accompanying
drawings.
[0043] To clarify the corresponding relation between each means of the inventions of claims
and the following embodiment, features of the present invention are described below
by adding a corresponding embodiment (one example) into the parentheses after each
means.
[0044] That is, the image synthesizing apparatus of claim 1 comprises first means (e.g.
step S3 in Figure 9) for obtaining a first characteristic point nearby a synthesis
position for synthesizing an object among the characteristic points projected onto
a first image, second means (e.g. step S2 in Figure 9) for obtaining first coordinates
of the first characteristic point on a three-dimensional coordinate system corresponding
to the first image, third means (e.g. step S6 in Figure 9) for obtaining second coordinates
of a second characteristic point corresponding to the first characteristic point on
a three-dimensional coordinate system corresponding to the second image among the
characteristic points projected onto the second image, fourth means (e.g. step S7
in Figure 9) for obtaining coordinate transform functions of the first and second
coordinates, fifth means (e.g. step S3 in Figure 9) for obtaining third coordinates
on a three-dimensional coordinate system corresponding to the first image at a synthesis
position for synthesizing the object with the first image, sixth means (e.g. step
S8 in Figure 9) for obtaining fourth coordinates on a three-dimensional coordinate
system corresponding to the second image by applying a coordinate transform function
to the third coordinates, and seventh means (e.g. step S10 in Figure 9) for synthesizing
the projected image of the object at a position corresponding to the fourth coordinates
of the second image.
[0045] The position detecting apparatus of claim 16 comprises first means (e.g. step S34
in Figure 12) for obtaining a first characteristic point nearby an object among the
characteristic points projected onto a first image, second means (e.g. step S32 in
Figure 12) for obtaining first coordinates of a first characteristic point on a three-dimensional
coordinate system corresponding to the first image, third means (e.g. step S36 in
Figure 12) for obtaining second coordinates of a second characteristic point corresponding
to the first characteristic point on a three-dimensional coordinate system corresponding
to the second image among the characteristic points projected onto the second image,
fourth means (e.g. step S33 in Figure 12) for obtaining third coordinates of the object
on a three-dimensional coordinate system corresponding to the first image, fifth means
(e.g. step S37 in Figure 12) for obtaining fourth coordinates of the object on a three-dimensional
coordinate system corresponding to the second image, sixth means (e.g. step S38 in
Figure 12) for obtaining coordinate transform functions of the first and second coordinates,
seventh means (e.g. step S39 in Figure 12) for obtaining fifth coordinates on a three-dimensional
coordinate system corresponding to the second image by applying the coordinate transform
functions to the third coordinates, and eighth means (e.g. step S40 in Figure 12)
for detecting the difference between the fourth and fifth coordinates.
[0046] The image synthesizing apparatus of claim 19 comprises image-pickup-device-position
computing means (e.g. step S61 in Figure 18) for computing the most-probable position
of an image pickup device when photographing each of a plurality of photographic images,
characteristic point position computing means (e.g. step S61 in Figure 18) for computing
the most-probable position of the characteristic point of a first object, virtual
projected position computing means (e.g. step S61 in Figure 18) for computing a virtual
projected position on which the most-probable position of a characteristic point is
projected when performing photography by using an image pickup device set at the most-probable
position, distortion value computing means (e.g. step S63 in Figure 18) for computing
a distortion value in accordance with the difference between a virtual projected position
and the position of the projected image of a characteristic point actually photographed
on each of a plurality of photographic images, correcting means (e.g. step S66 in
Figure 18) for correcting a position to which the projected image of a second object
is set in accordance with the distortion value computed by the distortion value computing
means, projected image computing means (e.g. step S67 in Figure 18) for computing
the projected image of the second object when photographing the second object from
an image pickup device present at the most-probable position by assuming that the
second object is located at the position corrected by the correcting means, and synthesizing
means (e.g. step S67 in Figure 18) for synthesizing the projected image of the second
object computed by the projected image computing means with each photographic image.
[0047] Of course, the above description does not mean that it is restricted to the description
of each means.
[0048] An embodiment of an image synthesizing apparatus of the present invention is described
below by referring to Figure 8.
[0049] As shown in Figure 8, the image synthesizing apparatus of the present invention has
an input section 11 to be operated by a user when the user inputs the synthesis position
of a CG image (image of the ball 5 or 6). The input section 11 is constituted with,
for example, a keyboard, a touch panel, a mouse, and a remote controller.
[0050] A control section 12 controls each section in order to synthesize CG data. Moreover,
the control section 12 has a memory 12A in which a program for synthesizing the CG
data is stored. A computing section 13 performs various operations for synthesizing
the CG data input from a CG data storing section 16 with the image data input from
an image data accumulating section 14. Moreover, the computing section 13 is constituted
so as to output an image synthesized with the CG data to a reproducing section 18.
The control section 12 and the computing section 13 are realized by, for example,
a microcomputer.
[0051] An image pickup section 2 uses, for example, a stereophonic video camera constituted
with a main video camera 2A and a sub-video camera 2B and is constituted so as to
pickup a plate 1 with the main video camera 2A and sub-video camera 2B and output
the picked-up image data to the image data accumulating section 14. The image data
accumulating section 14 is controlled by the control section 12, which accumulates
the image data input from the image pickup section 2 and outputs the data to the computing
section 13.
[0052] The CG data storing section 16 is controlled by the control section 12, which stores
CG data (image data of the balls 5 and 6) to be synthesized with the image data picked
up by the image pickup section 2 and outputs the CG data to the computing section
13. A display section 17 displays the image data picked up by the image pickup section
2 or the positional information of the plate 1 output from the computing section 13.
A reproducing section 18 reproduces image data with which the CG data input from the
computing section 13 is synthesized.
[0053] Then, operations of the embodiment thus constituted are described below by referring
to the flowchart in Figure 9.
[0054] In step S1, a user operates the input section 11 to command it to start pickup of
the plate 1. The input section 11 outputs a signal corresponding to the command to
the control section 12. The control section 12 makes the image data accumulating section
14 accumulate the image data sent from the image pickup section 2 in accordance with
the signal.
[0055] The image pickup section 2 (the main video camera 2A and sub-video camera 2B) picks
up the plate 1 while being moved by the user and outputs the picked-up image data
to the image data accumulating section 14, and the image data is stored in the image
data accumulating section 14. In this case, it is assumed that the number of images
picked up by the image pickup section 2 is N. Moreover, it is assumed that the identification
numbers k from 1 to N are provided for these images in time series and the time when
the k-th (k= 1,..., N) image 1A
K is formed is the k-th time. Furthermore, the control section 12 makes the memory
12A store the identification numbers k to use the memory 12A as a counter for synthesis
processing.
[0056] When pickup is completed, the control section 12 controls the image data accumulating
section 14 in step S2 to make the section 14 output the image data accumulated in
the section 14 to the computing section 13. The computing section 13 obtains a characteristic
point (e.g. pattern on the plate 1, defect on the plate 1, or other pattern) which
extremely changes compared to a point to which a brightness signal or color-difference
signal of the image data input from the image data accumulating section 14 is adjacent
and therefore, the characteristic point can be separated from other part of the image
data. In this case, the i-th characteristic point (pattern) is assumed as ai. In this
case, symbol i denotes an integer which is an identification number provided for each
pattern ai. Moreover, the computing section 13 compares the same patterns ai out of
the image data input from the main video camera 2A and the sub-video camera 2B at
the same time, calculates the parallax between the patterns, and obtains the three-dimensional
position (coordinates) of every pattern (characteristic point) ai. Because the three-dimensional
position is obtained by using the parallax between the cameras, this position is a
position on three-dimensional coordinates using the camera (image pickup section 2)
as an origin. That is, for example, the position in the three-dimensional coordinates
shown in Figure 10 to be described later is obtained.
[0057] For examples as shown in Figure 10, it is assumed that the position of the image
pickup section 2 at the first time is an origin O1 and the horizontal direction, vertical
direction, and depth direction of the image pickup section 2 are X-axis, Y-axis, and
Z-axis. The computing section 13 obtains the three-dimensional position (X1i, Y1i,
Z1i) of the every pattern ai on the image 1A
1 of the plate 1 at the first time.
[0058] Then, in step S3, the computing section 13 outputs the position of every pattern
ai and the first image 1A
1 to the display section 17 to make the section 17 display the position of every pattern
ai and the position of the first image 1A
1. The user operates the input section 11, and designates and inputs the three-dimensional
position (X1A, Y1A, Z1A) of the ball 5 for synthesizing the projected image 5A
1 of the ball 5 with the first image 1A
1 and the three-dimensional position (X1B, Y1B, Z1B) of the ball 6 for synthesizing
the projected image 6B
1 of the ball 6 with the first image 1A
1 based on the position information at the first time displayed in the display section
17.
[0059] Then, the computing section 13 obtains the three-dimensional vector (x2, y2, z2)
between the ball 5 and the pattern ai on every pattern ai in accordance with the following
Equation (7) and selects a predetermined number of patterns (e.g. 12 patterns) (in
the portion enclosed by the frame 21 in Figure 10) Aj (j = 1,...,12) in order of magnitudes
of the vectors starting with a vector having the smallest magnitude (starting with
a vector closest to the ball 5).

[0060] Then, the positions of the 12 selected patterns Aj (j = 1,...,12) are assumed as
(X1Aj, Y1Aj, Z1Aj) (j = 1,...,12).
[0061] Similarly, the computing section 13 obtains three-dimensional vectors (x3, y3, z3)
between the ball 6 and the pattern ai on all patterns ai in accordance with the following
Equation (8) and selects 12 patterns (in the portion enclosed by the frame 22 in Figure
10) Bj (j = 1,...,12) in order of magnitudes of the vectors starting with a vector
having the smallest magnitude (starting with a vector closest to the ball 6).

[0062] Then, the positions of the 12 selected patterns Bj (j = 1,...,12) are assumed as
(X1Bj, Y1Bj, Z1Bj) (j = 1,...,12).
[0063] Thus, a characteristic point nearby a synthesis position is obtained and then, step
S4 is started to perform image synthesis processing. That is, the computing section
13 obtains a two-dimensional synthesis position on the first image 1A
1 corresponding to a three-dimensional synthesis position. The two-dimensional synthesis
position is obtained by perspective-projection-transforming the three-dimensional
synthesis position. That is, when assuming the focal distance of the image pickup
section 2 as f, the two-dimensional position of the projected image 5A
1 of the ball 5 on the image 1A
1 at the first time corresponding to the three-dimensional position (X1A, Y1A, Z1A)
is shown as (X1A×f/Z1A, Y1A×f/Z1A). Similarly, the position of the projected image
6B
1 of the ball 6 on the two-dimensional image 1A
1 at the first time corresponding to the three-dimensional position (X1B, Y1B, Z1B)
is shown as (X1B×f/Z1B, Y1B×f/Z1B).
[0064] The control section 12 controls the CG data storing section 16 to output the CG data
(image data for the balls 5 and 6) stored in the CG data storing section 16 to the
computing section 13. Then, the computing section 13 synthesizes the CG data at the
obtained synthesis position.
[0065] Then, in step S5, the control section 12 sets an image identification number k to
2.
[0066] As shown in Figure 11, it is assumed that the position of the image pickup section
2 at the k-th time is an origin O
k, and the horizontal direction, vertical direction, and depth direction of the image
pickup section 2 are X-axis, Y-axis, and Z-axis. In step S6, the computing section
13 obtains the three-dimensional position (Xki, Yki, Zki) of the pattern ai (characteristic
point) at the k-th (in this case, k = 2) image 1A
k. The method for obtaining the position of the pattern ai is the same as the method
for obtaining the position of the pattern ai of the first image 1A
1.
[0067] As described above, because the patterns ai on the plate 1 can be separated from
each other, it is possible to identify that patterns (nearby patterns) Aj and Bj (j
= 1,..., 12) in the (k-1)-th three-dimensional coordinate system restored by the (k-1)-th
(in this case, 1st) image 1A
k-1 correspond to which patterns Aj and Bj (j = 1,...,12) in the k-th three-dimensional
coordinate system restored by the k-th image 1A
k. In this case, it is assumed that the positions of the patterns Aj and Bj (j = 1,...,12)
in the k-th three-dimensional coordinate system are (XkAj, YkAj, ZkAj) and (XkBj,
YkBj, ZkBj) (j = 1,...,12).
[0068] The above two coordinate systems view the same patterns Aj and Bj from different
angles. Therefore, in the (k-1)-th three-dimensional coordinate system, by applying
predetermined rotational transform (hereafter, the transform function of the rotational
transform is assumed as R
2) and predetermined rectilinear transform (hereafter, the transform function of the
rectilinear transform is assumed as S
2) to each pattern Aj in the (k-1)-th three-dimensional coordinate system, it is possible
to obtain the k-th three-dimensional coordinate system. Therefore, the following Equation
(9) is effected for each pattern Aj.

[0069] Therefore, in step S7, the computing section 13 obtains the transform functions R
2 and S
2 by substituting (X(k-1)Aj, Y(k-1)Aj, Z(k-1)Aj) and (XkAj, YkAj, ZkAj) for the above
Equation (9) on each pattern Aj.
[0070] Similarly, by applying predetermined rotational transform (hereafter, the transform
function of the rotational transform is assumed as R
3) and predetermined rectilinear transform (hereafter, the transform function of the
rectilinear transform is assumed as S
3) to each pattern Bj in the (k-1)-th three-dimensional coordinate system, it is possible
to obtain the k-th three-dimensional coordinate system. Therefore, the following Equation
(10) is effected for each pattern Bj.

[0071] Therefore, the computing section 13 obtains the transform functions R
3 and S
3 by substituting (X(k-1)Bj, Y(k-1)Bj, Z(k-1)Bj) and (XkBj, YkBj, ZkBj) for the above
Equation (10) on each pattern Bj.
[0072] As described above, when restoring the positions of the patterns Aj and Bj in a three-dimensional
space from two-dimensional image data picked up at a certain time, the restored position
includes any error. Therefore, when using, for example, the (k-1)-th three-dimensional
coordinate system as a criterion, the positions of the j-th patterns Aj and Bj are
not accurately present at (X(k-1)Aj, Y(k-1)Aj, Z(k-1)Aj) and (X(k-1)Bj, Y(k-1)Bj,
Z(k-1)Bj). Moreover, when using the k-th three-dimensional coordinate system as a
criterion, the positions of the j-th patterns Aj and Bj are not accurately present
at (XkAj, YkAj, ZkAj) and (XkBj, YkBj, ZkBj).
[0073] Therefore, the computing section 13 totalizes values obtained by squaring the magnitude
of the three-dimensional vector (x4, y4, z4) in the following Equation (11) on all
patterns Aj in accordance with the least-squares method to obtain (most-probable)
transform functions R
2 and S
2 for minimizing the total value.

[0074] By using the transform functions R
2 and S
2 obtained as described above, in step S8, the computing section 13 obtains the three-dimensional
position (XkA, YkA, ZkA) of the ball 5 at the k-th time in accordance with the following
Equation (12). This position is the position in the three-dimensional coordinate system
shown in Figure 11.

[0075] Similarly, the computing section 13 totalizes values obtained by squaring three-dimensional
vector (x5, y5, z5) on all patterns Bj in accordance with the least-squares method
to obtain (most-probable) transform functions R
3 and S
3 for minimizing the totalized value as shown by the following Equation (13).

[0076] By using the transform functions R
3 and S
3 obtained as described above, in step S8, the computing section 13 obtains the position
(XkB, YkB, ZkB) of the projected image 6B
k of the ball 6 at the k-th time from the following Equation (14). This position is
the position in the three-dimensional coordinate system shown in Figure 11.

[0077] In this connection, R
2, S
2, R
3, and S
3 depend on the positional relation between the image pickup sections 2 at the (k-1)-th
time and the k-th time. That is, R
2, S
2, R
3, and S
3 are functions of k, and R
2 equals R
2(k), S
2 equals S
2(k), R
3 equals R
3(k), and S
3 equals S
3(k).
[0078] Moreover, in step S9, the computing section 13 obtains three-dimensional vectors
(x6, y6, z6) between the ball 5 and the pattern ai on all patterns ai in accordance
with the following Equation (15) and selects 12 patterns (in the portion enclosed
by the frame 21 in Figure 11) Aj in the k-th three-dimensional coordinate system in
order of magnitudes of the vectors starting with a vector having the smallest magnitude
(starting with a vector closest to the ball 5) as shown by the following Equation
(15).

[0079] Moreover, the computing section 13 obtains three-dimensional vectors (x7, y7, z7)
between the ball 6 and the pattern ai on all patterns ai in accordance with the following
Equation (16) and selects 12 patterns (in the portion enclosed by the frame 22 in
Figure 11) Bj in the k-th three-dimensional coordinate system in order of magnitudes
of the vectors starting with a vector having the smallest magnitude (starting with
a vector closest to the ball 6).

[0080] Then, in step S10, the computing section 13 synthesizes the projected image 5A
k of the ball 5 at the position of (XkA×f/ZkA, YkA×f/ZkA) by using the relation of
the perspective projection transform in the k-th image 1A
k. Moreover, when there is any object other than the projected image 5A
k in the k-th image 1A
k at the image pickup section-2 side, the computing section does not synthesize the
projected image 5A
k if it is behind the object.
[0081] Similarly, the computing section 13 synthesizes the projected image 6B
k of the ball 6 at the position of (XkB× f/ZkB, YkB×f/ZkB) by using the relation of
the perspective projection transform in the k-th image 1A
k. Also in this case, when there is any object other than the projected image 6B
k in the k-th image 1A
k at the image pickup section-2 side, the computing section 13 does not synthesize
the projected image 6B
k if it is behind the object.
[0082] Then, in step S11, the control section 12 decides whether synthesis processing is
completed on the whole image data picked up by the image pickup section 2. Unless
the processing is completed (for k ... N), the control section 12 starts step S12
to increment the identification number k of an image by 1 (k = k + 1), and returns
to step S4 to continue the synthesis processing. When the processing is completed
(for k = N), the control section 12 starts step S13 and the computing section 13 outputs
the image data undergoing the synthesis processing to the reproducing section 18 to
make the section 18 reproduce the data (display the data).
[0083] For example, when positional relation between the patterns ai nearby the balls 5
and 6 (for example, 10 cm separate from the balls 5 and 6) is always the same, a person
senses that the balls 5 and 6 are stationary. However, even if the positional relation
between the patterns ai present far from the balls 5 and 6 (for example, 100 m separate
from the balls 5 and 6) changes, the person does not sense the change of the positional
relation.
[0084] In the case of the present invention, a pattern nearby a synthesis position is selected
without considering a pattern present far from the synthesis position (that is, a
pattern not to be sensed by a person) to obtain the rotational transform and rectilinear
transform for the pattern. Therefore, it is possible to synthesize an image so that
the balls 5 and 6 seem to be stationary on the plate 1.
[0085] In the case of the above embodiment, the stationary balls 5 and 6 are synthesized
with the plate 1. However, it is also possible to synthesize the moving balls 5 and
6 with the plate 1. In this case, it is necessary to synthesize the projected images
of the balls 5 and 6 at the synthesis position of the balls 5 and 6 to be synthesized
in the k-th three-dimensional coordinate system obtained in step S8 in Figure 9 by
using values obtained by adding the three-dimensional vector showing each movement
at the synthesis position as new positions of the balls 5 and 6.
[0086] Moreover, in the case of the above embodiment, relatively small objects such as the
balls 5 and 6 are synthesized. However, it is also possible to synthesize a large
object. For example, to synthesize a large rectangular parallelepiped, by designating
eight vertexes of the rectangular parallelepiped, it is possible to obtain the sides
for connecting the vertexes and a plane enclosed by the sides. The rectangular parallelepiped
is synthesized by assuming these eight vertexes as independent objects. Because eight
points are determined in each continuous image, it is possible to synthesize the rectangular
parallelepiped by connecting these points by straight lines and using the points connected
by the straight lines as sides and moreover, using the range enclosed by the sides
as a plane.
[0087] In the case of the above embodiment, images of the balls 5 and 6 formed through CG
are synthesized. However, it is also possible to obtain the positional relation between
objects (objects to be actually photographed) actually present on the plate 1. Then,
the operation is described below by referring to the flowchart in Figure 12.
[0088] As shown in Figure 13, it is assumed that the position of the image pickup section
2 at the first time is an origin O1 and the horizontal direction, vertical direction,
and depth direction of the image pickup section 2 are X-axis, Y-axis, and Z-axis.
Existent balls 31 and 32 move on the plate 1. In step S31, the image pickup section
2 picks up the plate 1 while being moved by, for example, a user. Similarly to the
case of the above embodiment, it is assumed that the number of images picked up by
the image pickup section 2 within a pickup time is N. Moreover, identification numbers
k from 1 to N are provided for these images in time series and it is assumed that
the time when the k-th (k = 1,...,N) image 1A
k is formed is the k-th time. Moreover, the control section 12 makes a memory 12A store
the identification numbers k and uses the memory 12 as a synthesis-processing counter.
[0089] When image pickup by the image pickup section 2 is completed, the computing section
13 obtains the three-dimensional position (X1i, Y1i, Z1i) of every pattern (characteristic
point) ai on the plate 1 at the first time in step S32. Moreover, the computing section
13 obtains the three-dimensional position (X1C, Y1C, Z1C) of the ball 31 and the three-dimensional
position (X1D, Y1D, Z1D) of the ball 32 at the first time in step S33.
[0090] The computing section 13 obtains three-dimensional vectors (x8, y8, z8) between the
ball 31 and the pattern ai on all patterns ai in step S34 in accordance with the following
Equation (17) and selects 12 patterns (in the portion enclosed by the frame 41 in
Figure 13) Cj in the first three-dimensional coordinate system in order of magnitudes
of the vectors starting with a vector having the smallest magnitude (starting with
a vector closest to the ball 31).

[0091] Moreover, the positions of the 12 selected patterns Cj (j = 1,...,12) are assumed
as (X1Cj, Y1Cj, Z1Cj) (j = 1,...,12).
[0092] Similarly, the computing section 13 obtains three-dimensional vectors (x9, y9, z9)
between the ball 32 and the pattern ai on all patterns ai in accordance with the following
Equation (18) and selects 12 patterns (in the portion enclosed by the frame 42 in
Figure 13) Dj in the first three-dimensional coordinate system in order of magnitudes
of the vector starting with a vector having the smallest magnitude (starting with
a vector closest to the ball 32).

[0093] Then, positions of the 12 selected patterns Dj (j = 1,...,12) are assumed as (X1Dj,
Y1Dj, Z1Dj) (j = 1,...,12).
[0094] Then, in step S35, the control section 12 sets the identification number k of image
data to 2.
[0095] Similarly, as shown in Figure 14, it is assumed that the position of the image pickup
section 2 at the k-th time (in this case, k = 2) is an origin Ok, and the horizontal
direction, vertical direction, and depth direction of the image pickup section 2 are
X-axis, Y-axis, and Z-axis. Moreover, the computing section 13 obtains the three-dimensional
position (Xki, Yki, Zki) of the pattern ai in the k-th image 1A
k in step S36.
[0096] As described above, the patterns ai on the plate 1 can be separated from each other,
it is possible to identify that the patterns Cj and Dj (j = 1,...,12) in the (k-1)-th
three-dimensional coordinate system restored from the (k-1)-th image 1A
k-1 correspond to which patterns Cj and Dj (j = 1,...,12) in the k-th three-dimensional
coordinate system restored from the k-th image 1A
k. In this case, positions of the patterns Cj and Dj (j = 1,...,12) in the k-th three-dimensional
coordinate system are assumed as (XkCj, YkCj, ZkCj) and (XkDj, YkDj, ZkDj) (j = 1,...,12).
[0097] The computing section 13 obtains the position (XkC, YkC, ZkC) of the ball 31 and
the position (XkD, YkD, ZkD) of the ball 32 at the k-th time in step S37.
[0098] By applying predetermined rotational transform (hereafter, the transform function
of the rotational transform is assumed as R
4) and predetermined rectilinear transform (hereafter, the transform function of the
rectilinear transform is assumed as S
4) to the pattern Cj in the (k-1)-th three-dimensional coordinate system, it is possible
to obtain the k-th three-dimensional coordinate system. Moreover, to restore the position
of the pattern Cj in a three-dimensional space, the computing section 13 totalizes
values obtained by squaring the magnitude of three-dimensional vector (x12, y12, z12)
on all patterns Cj by the least-squares method in accordance with the following Equation
(19) to obtain (most-probable) transform functions R
4 and S
4 for minimizing the total value in step S38 by considering that the restored position
includes any error.

[0099] The computing section 13 obtains a position (XkC', YkC', ZkC') when the ball 32 is
stationary in accordance with the following Equation (20) in step S39 by using the
transform functions R
4 and S
4 thus obtained.

[0100] Therefore, the three-dimensional vector (xkc, ykc, zkc) in the following Equation
(21) shows the movement of the ball 31 between the (k-1)-th time and the k-th time.
This operation is performed in step S40.

[0101] Similarly, by applying predetermined rotational transform (hereafter, the transform
function is assumed as R
5) and predetermined rectilinear transform (hereafter, the transform function is assumed
as S
5) to the pattern Dj in the (k-1)-th three-dimensional coordinate system, it is possible
to obtain the k-th three-dimensional coordinate system. To restore the position of
the pattern Dj in a three-dimensional space, the computing section 13 totalizes values
obtained by squaring the magnitude of the three-dimensional vector (x13, y13, z13)
in the following Equation (22) on all patterns Dj by the least-squares method to obtain
(most-probable) transform functions R
5 and S
5 for minimizing the total value by considering that the restored position includes
any error.

[0102] The computing section 13 obtains a position (XkD', YkD', ZkD') when the ball 32 is
stationary in accordance with the following Equation (23) by using the transform functions
R
5 and S
5 thus obtained.

[0103] Therefore, it is possible to obtain the three-dimensional vector (xkd, ykd, zkd)
in the following Equation (24), that is, the movement of the ball 32 between the (k-1)-th
time and the k-th time.

[0104] Then, the computing section 13 obtains three-dimensional vectors (x10, y10, z10)
between the ball 31 and the pattern ai on all patterns ai in step S41 as shown by
the following Equation (25) and selects 12 patterns (in the portion enclosed by the
frame 41 in Figure 14) Cj in the k-th three-dimensional coordinate system in order
of magnitudes of the vectors starting with a vector having the smallest magnitude
(starting with a vector closest to the ball 31).

[0105] Moreover, the computing section 13 obtains three-dimensional vectors (x11, y11, z11)
between the ball 32 and the pattern ai on all patterns ai as shown by the following
Equation (26) and selects 12 patterns (in the portion enclosed by the frame 42 in
Figure 14) Dj in the k-th three-dimensional coordinate system in order of magnitudes
of the vectors starting with a vector having the smallest magnitude (starting with
a vector closest to the ball 32).

[0106] Then, in step S42, the control section 12 decides whether synthesis processing is
completed on the whole image data picked up by the image pickup section 2. When the
processing is not completed (for k ... N), the control section 12 starts step S43
to increment the identification number k of an image by 1 (k = k + 1), and returns
to step S36 to continue the synthesis processing. When the processing is completed
(for k = N), the computing section 13 starts step S44 to make the display section
17 display movement values (xkc, ykc, zkc) and (xkd, ykd, zkd) at each time.
[0107] In the case of the above first embodiment, a characteristic point uses a two-dimensional
object such as the pattern ai on the plate 1. However, it is also possible to use,
for example, a side of a rectangular parallelepiped three-dimensionally arranged.
[0108] Moreover, in the case of the first embodiment, a characteristic point is selected
through the operation by the computing section 13. However, it is also possible that,
for example, a user selects the characteristic point by operating the input section
11 during processing.
[0109] Furthermore, in the case of the first embodiment, 12 patterns (characteristic points)
Aj and Bj nearby a synthesis position are selected. However, for example, it is also
possible to obtain a rotational transform function and a rectilinear transform function
by selecting 20 patterns close to a synthesis position, providing a weight larger
than that of 8 remaining patterns for 12 patterns closer to the synthesis position
out of 20 patterns, and using the least-squares method.
[0110] The obtained rotational transform function and rectilinear transform function serve
as a rotational transform function and a rectilinear transform function having a relatively
large error for 8 relatively remote patterns and serve as a rotational transform function
and a rectilinear transform function having a completely controlled error for the
12 patterns close enough. This is favorable because this corresponds to the human-eye
characteristic of recognizing the positional relation between characteristic points
separate from each other to a certain extent (the above 8 patterns) at a relatively
rough accuracy and recognizing the positional relation between characteristic points
close enough to each other (the above 12 patterns) at a high accuracy. Of course,
the present invention does not restrict the number of characteristic points to 12
or 20.
[0111] In the case of the first embodiment, the picked up plate 1 is synthesized with CG
data so as to simplify the description. Actually, however, the plate 1 is a real image
photographed by a camera and a characteristic point in the plate 1 corresponds to
a characteristic point such as an edge in the real image. For example, when there
is a desk or wall in a photographic image, a corner of the desk or stain (dust or
the like) on the wall serves as a characteristic point.
[0112] For example, it is assumed to put a vase formed through CG on a real-image desk obtained
by photographing an actual room in which a real desk is present by a camera. First,
it is possible to obtain three-dimensional information (characteristic point) from
a corner of the desk. Moreover, a corner of a window frame of the room or a corner
of a fluorescent lamp on the ceiling of the room is detected as three-dimensional
information (characteristic point). Furthermore, when putting the vase formed through
CG on the desk, the vase formed through CG is synthesized with the real image in accordance
with the three-dimensional information obtained from a characteristic point (e.g.
the corner of the desk or the like) present nearby the position where the vase is
put. In this case, however, the three-dimensional information obtained from a remote
characteristic point (e.g. the corner of the window frame of the room or the corner
of the fluorescent lamp on the ceiling of the room) is ignored.
[0113] In the case of the above embodiment, a small ball formed through CG is synthesized
with a photographic image. Moreover, to synthesize a large rectangular parallelepiped,
eight vertexes of the rectangular parallelepiped are assumed as independent objects,
each vertex is synthesized with a characteristic point nearby the vertex so that the
positions coincide with each other, and sides and planes are synthesized at positions
where these vertexes are connected by straight lines. That is, because vertexes are
positioned, a person does not sense that the vertexes of the rectangular parallelepiped
are displaced. However, sides and planes are not accurately positioned.
[0114] As a result, when processing a photographic image string obtained by continuously
photographing a first object and thereby, generating a new photographic image string
showing as if a second object is present at the string, that is, when synthesizing
the second object with the original photographic image string and thereby, generating
a synthesized image string, the synthesized image string may be unnatural because
a synthesis position is slightly displaced in each synthesized image.
[0115] That is, when obtaining the position and attitude (direction) of an image pickup
device in a three-dimensional real space and the position of a characteristic point
in a three-dimensional real space at each time, these obtained values do not show
true values but they include errors.
[0116] A projected image at a certain time Th is noticed. The projected position of a characteristic
point when photographing the characteristic point from the obtained position and attitude
(direction) of the image pickup device including errors but not showing true values
at the time Th by assuming that the characteristic point is present at the position
of the obtained characteristic point including errors but not showing a true value
is referred to as a virtual projected position.
[0117] In fact, the position of the characteristic point appearing on a photographic image
Ph photographed at the time Th is slightly displaced from the virtual projected position.
[0118] Therefore, in the case of the second embodiment to be described below, the displacement
value (distortion value) is obtained. The distortion value depends on the position.
Moreover, because the distortion value depends on time, it is obtained for each time.
In other words, the distortion value is the function of position and time.
[0119] The position (virtual position) of the object (second object) to be synthesized is
determined by an operator in accordance with the relation between the position of
the second object and the position of the above obtained characteristic point.
[0120] Similarly to the case of the first embodiment, when obtaining the projected image
of the second object from the obtained position and attitude (direction) of the image
pickup device at the time when assuming that the second object is present at this
virtual position, it is displaced from the projected position of a characteristic
point in the actually-photographed photographic image Ph.
[0121] In the case of the second embodiment, the virtual position of the second object determined
by the operator is distorted by a value equal to the distortion value obtained above.
Moreover, the projected image of the second object is obtained by assuming that the
second object is present at the distorted position. Thus, the position of the projected
image of the second object coincides with that of the projected image of the characteristic
point in the actually-photographed photographic image Ph.
[0122] Then, geometry about general computer vision is described below before specifically
describing the second embodiment.
[0123] It is assumed that the position and attitude (direction) of an image pickup device
(corresponding to the image pickup section 2 in Figure 8) is present at a position
moved from the origin of world coordinates due to the rotation of a matrix R and the
translation of a vector S. In this case, a point at a position (X, Y, Z) on the basis
of the world coordinates has coordinates (XX, YY, ZZ) shown in the following Equation
(27) in the case of a coordinate system based on the above image pickup device. This
state is shown in Figure 15.

[0124] Therefore, the position (U, V) of the projected image of the above point in the photographic
image photographed by the above image pickup device is shown by the following Equations
(28) and (29). This state is shown in Figure 16.

[0125] Where,

[0126] Symbol f in the Equations (28) and (29) denotes the focal distance of the image pickup
device.
[0127] Then, points in a plurality of photographic images and points in the three-dimensional
real spaces are assumed.
[0128] A plurality of photographic images are obtained by performing photography while moving
the image pickup device. It is assumed that photography is performed at H times such
as T1, T2, T3,..., TH. Moreover, it is assumed that a photographic image photographed
at the time Th is Ph. Furthermore, it is assumed that the position and attitude (direction)
of the image pickup device at the time Th is moved from the origin of the world coordinates
due to rotation matrix Rh and parallel displacement vector Sh. In this case, h = 1,...,H.
[0129] Furthermore, it is assumed that each of the positions of the points (J points) in
the three-dimensional real spaces is (Xj, Yj, Zj) on the basis of the world coordinates.
That is, it is assumed that the position of the j-th point is (Xj, Yj, Zj). In this
case, j = 1,...,,J. Furthermore, it is assumed that each point is stationary in a
three-dimensional real space.
[0130] Furthermore, it is assumed that the position of the projected image of the j-th point
appearing on the photographic image Ph is (Uhj, Vhj).
[0131] Because of the same as the case of the Equations (27) to (29), the following Equations
(30) to (32) are derived.

[0132] Where, j = 1,...,J, and h = 1,...,H.

[0133] Where,

j = 1,...,J, and h = 1,...,H.
[0134] In this case, (XXhj, YYhj, ZZhj) denotes the position of the j-th point on a coordinate
system based on the image pickup device at the time Th.
[0135] It is assumed that the position and attitude (direction) of the image pickup device
and the position (Xj, Yj, Zj) of the above point in a three-dimensional real space
at each time are unknown. In this case, it is possible to obtain these unknown values
from the photographic image Ph (h = 1,...,H) at each time. That is, the position (Uhj,
Yhj) of the projected image of the j-th point appearing on the photographic image
Ph can be obtained by checking the image Ph. It is possible to obtain unknown parameters
(rotation matrix Rh, parallel displacement vector Sh, and Xj, Yj, Zj) by substituting
the obtained position (Uhj, Vhj) for the Equations (31) and (32). Where, h = 1,...,H,
j= 1,...,J.
[0136] When solving the Equations (31) and (32) by substituting the value of (Uhj, Vhj)
for the Equations (31) and (32), the indeterminacy of how to put the world coordinates
remains. However, this is not important. For example, it is possible to make the position
and attitude (direction) of the image pickup device at the first time T1 coincide
with the world coordinates. In other words, it is possible to solve the Equations
(31) and (32) under the condition that R
1 is a zero matrix and S
1 is a zero vector.
[0137] Moreover, in the case of an image pickup device using a wide angle lens (fish-eye
lens), a photographic image taken by the device may be distorted. In this case, it
is necessary to previously measure a distortion value (to previously calibrate a camera).
By multiplying a distorted photographic image by the inverse number of the distortion
value, it is possible to form an undistorted photographic image. Moreover, by using
the above method for the undistorted photographic image, it is possible to obtain
the position and attitude (direction) of the image pickup device and the position
(Xj, Yj, Zj) of the above point in a three-dimensional real space at each time from
the Equations (31) and (32).
[0138] By solving the Equations (31) and (32), it is possible to obtain the position and
attitude (direction) of the image pickup device in a three-dimensional real space
and the position of the above point in the three-dimensional real space at each time.
However, these obtained values do not show true values. As described above, errors
are always included in measured data in general. The position and attitude (direction)
of the image pickup device and the position (Xj, Yj, Zj) of the j-th point at each
time (Th) are used as unknown parameters and these unknown parameters are obtained
from observed data (Uhj, Vhj) in accordance with the Equations (31) and (32). In this
case, because errors are included in the observed data (Uhj, Vhj), errors are also
included in the position and attitude (direction) of the image pickup device in a
three-dimensional real space and the position of the above point in the three-dimensional
real space obtained by solving the Equations (31) and (32).
[0139] Figure 17 shows an example of the structure of the image synthesizing apparatus of
the second embodiment. In Figure 17, a processing circuit 32 performs various types
of operations in accordance with a program stored in a program memory 31. A data memory
33 is a memory for storing the data currently processed by the processing circuit
32. A frame memory 34 stores the image data to be displayed on an image display unit
35. An input unit 36 is constituted with, for example, a keyboard and a mouse and
operated to input various commands. An input/output terminal 37 is connected with
a not-illustrated external unit to transfer data. A bus line 38 is a bus for connecting
these units each other.
[0140] Then, operations of the image synthesizing apparatus of the second embodiment are
described below by referring to the flowchart in Figure 18. The processing in Figure
18 is mainly performed by the processing circuit 32.
[0141] It is assumed to put (synthesize) a building (second object: shown as a building
91 in Figure 20) formed through CG between two real buildings (first objects: shown
as a building 71 and a building 81 in Figure 19). Then, in step S61, the above two
real buildings (first objects) are photographed while moving a video camera (image
pickup device). The image data for the two buildings is stored in the data memory
33 through the bus line 38 from the input/output terminal 37. In this case, because
the position of the projected image of a building in each photographic image moves
with passage of time, it is also necessary to displace the position of the projected
image of the building (second object) to be synthesized in the photographic image.
This state is shown in Figures 19 to 23.
[0142] That is, as shown in Figure 19, it is assumed that the position of the video camera
(image pickup device) is 61-1 at the first time T1. At the next time T2, the video
camera moves to the position 61-2. Similarly, at the time Th (h = 3, 4,..., H), the
position of the video camera moves to 61-h. Thereby, the above two real buildings
(first objects) 71 and 81 are picked up. It is the final object to synthesize the
second object (building 91) between the buildings 71 and 81, that is, obtain the same
synthesized image as the photographic image just obtained by photographing the three
buildings 71, 91, and 81 shown in Figure 20 while moving the video camera from the
position 61-1 to the position 61-H.
[0143] Figure 21 shows photographic images P1, P2,..., Ph,..., PH taken by the video camera
at the times T1, T2,..., Th,. .., TH. Symbols 71-1, 71-2,..., 71-h,..., 71-H denote
projected images of the above real building 71 at various times. Symbols 81-1, 81-2,...,
81-h,..., 81-H denote projected images of the above real building 81 at various times.
[0144] Then, the position and attitude (direction) of the video camera in a three-dimensional
real space and positions of J characteristic points (first characteristic points)
of the first objects 71 and 81 in the three-dimensional real space when photographing
each photographic image Ph (Figure 21) at each time are obtained. As described above,
a characteristic point is a point at which brightness or color suddenly changes. For
example, a characteristic point is a corner of a rectangular parallelepiped (e.g.
building) or black point on a white plane (e.g. black dust attached to white wall).
Specifically, corners 72 to 75 and 82 to 85 of the buildings 71 and 81 in Figure 19
are first characteristic points. In this connection, the plane enclosed by the corners
72 to 75 is the front of the building 71 and the plane enclosed by the corners 82
to 85 is the front of the building 81.
[0145] That is, the position (U1j, V1j) of the projected image of the j-th characteristic
point is obtained out of the first characteristic points (total of J characteristic
points) appearing on the photographic image P1 at the time T1. Moreover, the position
(U2j, V2j) of the projected image of the j-th characteristic point is obtained out
of the first characteristic points appearing on the photographic image P2 at the time
T2. Similarly, the position (Uhj, Vhj) of the projected image of the j-th characteristic
point is obtained out of the first characteristic points appearing on the photographic
image Ph at the time Th (h = 3,...,H).
[0146] Furthermore, rotation matrix Rh, parallel displacement vector Sh, and (Xj, Yj, Zj)
are obtained for h = 1,...,H and j = 1,...,J by substituting the position (Uhj, Vhj)
for the following Equation (33). The obtained data is stored in the data memory 33.
[Equation 33]
[0147] 
[0148] Where,

[0149] The obtained rotation matrix Rh and parallel displacement vector Sh show the position
and attitude (direction) of the video camera at the time Th based on the world coordinates.
The obtained (Xj, Yj, Zj) shows the position of the j-th characteristic point based
on the world coordinates.
[0150] Thus, it is possible to obtain the position and attitude (direction) of the video
camera in a three-dimensional real space and positions of the characteristic points
(first characteristic points) of the buildings 71 and 81 serving as first object in
the three-dimensional real space when photographing each of the photographic images
Ph (Figure 21) at each time Th.
[0151] It is assumed that the corner 75 (Figure 19) which is one of the first characteristic
points corresponds to the k-th characteristic point. Symbol k denotes any numerical
value of 1 to J. In accordance with the processing in step S61, the position (Xk,
Yk, Zk) of the k-th characteristic point based on the world coordinates is obtained.
Of course, the position does not show a true value but errors are included. In this
connection, the corner 75 is the corner at the front top right of the real building
71.
[0152] Moreover, the photographic image Ph at the time Th is a photographic image photographed
when the video camera is moved from the origin of the world coordinates due to the
rotation of the matrix Rh and the translation of the vector Sh. Therefore, the matrix
Rh and the vector Sh are also obtained. Of course, the above states {position and
attitude (direction) shown by the rotation matrix Rh and parallel displacement vector
Sh} do not show true values but errors are included.
[0153] Thus, because the positions of the two real buildings (first objects) 71 and 81 in
a three-dimensional real space are obtained through the processing in step S61, the
data for the position (Xj, Yj, Zj) is supplied to an image display unit 35 through
the frame memory 34 and displayed in step S62. By viewing the indication, an operator
(person performing the synthesis operation) designates a position to which the building
(second object) 91 formed through CG (position in a virtual three-dimensional real
space) is set by operating the input unit 36. The operator determines the above operation
while considering the positions of the two real buildings (first objects) 71 and 81
in a three-dimensional real space. The determined positions are stored in the data
memory 33.
[0154] Specifically, as shown in Figure 20, because the positions of the corners 72 to 75
and the corners 82 to 85 serving as first characteristic points are obtained in the
world coordinates, the building (second object) 91 formed through CG is put between
the positions. That is, it is necessary to set the building (second object) 91 formed
through CG so that the plane enclosed by the corners 75, 74, 83, and 82 serves as
the front of the building (second object) 91 formed through CG (so that the top left
corner 92 and the bottom left corner 93 of the building 91 correspond to the top right
corner 75 and the bottom right corner 74 of the building 71 and the top right corner
95 and bottom right corner 94 of the building 91 correspond to the top left corner
82 and the bottom left corner 83 of the building 81). Thus, the position of the building
(second object) 91 formed through CG is determined.
[0155] That is, the building (second object) 91 formed through CG is virtually set so that
the front top left of the building (second object) 91 formed through CG is brought
to the position (Xk, Yk, Zk) based on the world coordinates (Figure 20). In other
words, the front top left position of the building (second object) 91 formed through
CG is (Xk, Yk, Zk). In this connection, the position (Xk, Yk, Zk) is the position
of the corner 75 serving as the k-th characteristic point. Thereby, the real building
71 and the building (second object) 91 formed through CG are set so that the front
top right of the building 71 contacts the front top left of the building 91.
[0156] Then, the corner 75 (k-th characteristic point) which is one of the first characteristic
points is considered below. The photographic image Ph at the time Th includes the
projected image of the corner 75 which is the k-th characteristic point. The position
of the projected image is shown as (Uhk, Vhk). Therefore, the following Equations
(34) and (35) are effected.

[0157] In this case, Rh, Sh, Xk, Yk, and Zk are values obtained by minimizing the Equation
(33). The right and left sides of the Equations (34) and (35) have almost equal values.
As previously described, however, they are not strictly equal to each other. However,
the position (UUhk, VVhk) of the projected image at the front top left of the building
91 completely meets the following Equations (36) and (37).

[0158] Where,

[0159] That is, as shown in Figure 22, it is considered to photograph the building (second
object) 91 formed through CG with the video camera by assuming that the front top
left of the building 91 is present at the position (Xk, Yk, Zk) based on the world
coordinates. The position and attitude (direction) of the video camera are shown by
the rotation matrix Rh and parallel displacement vector Sh at the time Th. Therefore,
the position of the projected image at the front top left of the building 91 results
in the position (UUhk, VVhk) in the photographic image at the time Th shown by the
Equations (36) and (37). Where, h = 1,...,H.
[0160] As a result, (Uhk, Vhk) is not equal to (UUhk, VVhk). This Equation represents the
following.
[0161] It is assumed that an operator arranges the real building 71 and the building 91
formed through CG so that the front top right of the building 71 contacts the front
top left of the building 91, forms the projected image of the virtual building 91,
and synthesizes an actually-photographed photographic image. The projected image at
the front top right of the building 71 at the time Th is located at (Uhk, Vhk) (Figure
21). Moreover, the projected image at the front top left of the artificially-formed
building 91 is located at (UUhk, VVhk) (Figure 22). Therefore, the projected image
at the front top right of the real building 71 at the time Th does not coincide with
the projected image at the front top left of the virtual building 91. When a person
views the synthesized image of them, he does not sense that the state is photographed
in which the front top right of the real building 71 contacts the front top left of
the building 91 formed through CG.
[0162] Moreover, it is not guaranteed that the difference between the right and left sides
of the Equations (34) and (35) is constant every time Th. Therefore, when a person
continuously views an image synthesized every time, he feels as if the interval between
the front top right of the real building 71 and the front top left of the building
91 formed through CG swings.
[0163] Because Figure 23 shows synthesized images under an ideal state free from errors,
(Uhk, Vhk) is equal to (UUhk, VVhk). In fact, however, (Uhk, Vhk) is not equal to
(UUhk, VVhk).
[0164] Therefore, the Rh, Sh, Xj, Yj, and Zj obtained in step S61 and the position (Uhj,
Vhj) of the projected image of the j-th characteristic point in the photographic image
Ph do not completely meet the Equations (31) and (32). That is, the following Equations
(38) and (39) are effected. Where, h = 1,...,H, j = 1,...,J.

[0165] Where,

[0166] Thus, the processing circuit 32 reads each time Th and the data for characteristic
points from the data memory 33 in step S63, computes the following Equations (40)
to (44) for the time Th and the characteristic point data, obtains the coordinates
(XXhj, YYhj, ZZhj) and the displacement value (δ XXhj, δ YYhj) of each characteristic
point based on the video camera, and stores the coordinates and displacement value
in the data memory 33.

[0167] Where,


[0168] That is, the position (X, Y, Z) based on the world coordinates is transformed into
the position (XXh, YYh, ZZh) in a coordinate system based on the video camera at the
time Th in accordance with the transform formulas shown in the following Equations
(45) to (47).

[0169] The point located at (XXh, YYh, ZZh) is projected on the position (f · XXh/ZZh, f
· YYh/ZZh) in the photographic image Ph.
[0170] The corner 75 (k-th characteristic point) shown in Figure 12 is considered below.
The position of the characteristic point becomes the position (XXhk, YYhk, ZZhk) shown
by the following Equations (48) to (50) in the coordinate system based on the video
camera at the time Th.

[0171] Therefore, if an ideal photographing state free from errors is set, the position
(XXhk, YYhk, ZZhk) and the position (Uhk, Vhk) of the projected image of the k-th
characteristic point in the photographic image Ph have the relation between the following
Equations (51) and (52).

[0172] However, because errors are actually present, the equal signs shown in the Equations
(51) and (52) are not effected. That is, errors equivalent to (δ XX, δ YY) shown in
the following Equations (53) and (54) are produced.

[0173] Therefore, the errors (δ XX, δ YY) are computed in accordance with the Rh, Sh, Xk,
Yk, and Zk obtained in step S61, measured values (Uhk, Vhk), and the Equations (48)
to (50) and the Equations (53) and (54).
[0174] It is determined in step S62 to imaginarily set the corner 92 at the front top left
of the building (second object) 91 formed through CG to the position (Xk, Yk, Zk)
based on the world coordinates. That is, the corner 92 is set to the position (XXhk,
YYhk, ZZhk) shown by the Equations (48) to (50) in the coordinate system based on
the video camera at the time Th. The corner 92 is projected on the position (UUhk,
VVhk) shown by the following Equations (55) and (56) in the photographic image at
the time Th.

[0175] In this connection, the Equations (48) to (50) and the Equations (55) and (56) are
equivalent to the Equations (36) and (37). The position (UUhk, VVhk) shown by the
Equations (55) and (56) is different from the position (Uhk, Vhk) of the projected
image of the k-th actual characteristic point. This is a positional displacement becoming
a problem.
[0176] Therefore, in the case of the second embodiment, the portion of the building (second
object) 91 formed through the CG shown by the position (XXhk, YYhk, ZZhk) in the coordinate
system based on the video camera at the time Th is displaced by the value shown by
the Equations (53) and (54) before forming the projected image of the second object.
That is, it is determined in step S62 to set the corner 92 at the front top left of
the building 91 to the position (XXhk, YYhk, ZZhk) in the coordinate system based
on the video camera at the time Th. However, the position is displaced by the value
shown by the Equations (53) and (54) so that it is brought to (XXhk + δ XX, YYhk +
δ YY, ZZhk). Thus, by displacing the position of the corner 92 at the front top left
of the building 91, the position of the projected image of the corner 92 at the front
top left of the artificially-formed building 91 at the time Th is brought to the position
shown by the following Equations (57) and (58).

[0177] The position (UUhk, VVhk) is just the same as the position (Uhk, Vhk) of the projected
image of the corner 75 (k-th characteristic point) because the following Equations
(59) and (60) are effected.

[0178] In short, it is decided in step S61 that the k-th characteristic point is present
at the position (Xk, Yk, Zk) based on the world coordinates. This position is the
position (XXhk, YYhk, ZZhk) shown by the Equations (48) to (50) in the coordinate
system based on the video camera at the time Th. This value is displaced by (δ XX,
δ YY) shown by the Equations (53) and (54) from the position (Uhk, Vhk) of the projected
image of the k-th characteristic point projected on the photographic image Ph at the
time Th in a three-dimensional real space. Therefore, to set the object (corner 92
at the front top left of the building 91) to be synthesized to the position (XXhk,
YYhk, ZZhk) in the coordinate system based on the video camera at the time Th, a projected
image is formed by assuming that the projected image is present at a position displaced
by (δ XX, δ YY). Thereby, the position of the projected image coincides with that
of the projected image of the actually-photographed object (corner 75 at the front
top right Of the building 71).
[0179] In the case of the above specific example, the corner 75 (k-th characteristic point)
is described. The same is true for characteristic points other than the k-th characteristic
point. In the case of an object (or a part of the object) to be synthesized present
at a position just coinciding with the first characteristic points (first,...,j-th
characteristic points), it is necessary to compute (δ XX, δ YY) which is the displacement
value (distortion value) of a corresponding characteristic point and form the projected
image of the object by assuming that the projected image is present at a position
displaced by (δ XX, δ YY), as described above.
[0180] However, when the first characteristic points are not present at the position of
the object (or a part of the object) to be synthesized, it is necessary to obtain
the displacement value (distortion value) (δ XX, δ YY) through interpolation from
a nearby first characteristic point.
[0181] Therefore, in step S64, the processing circuit 32 reads the characteristic point
(XXhj, YYhj, ZZhj) at each time Th from the data memory 33, performs Delaunay division
by using the characteristic point as a mother point, obtains a Delaunay convex polygon,
and stores the polygon in the data memory 33.
[0182] That is, the position of the j-th characteristic point in the coordinate system based
on the video camera at the time Th is assumed as (XXhj, YYhj, ZZhj). This position
can be obtained from the Equations (40) to (42) by using the Rh, Sh, Xj, Yj, and Zj
obtained in step S61.
[0183] Then, the displacement value (distortion value) (δ XXhj, δ YYhj) at (XXhj, YYhj,
ZZhj) is obtained by using the Equations (43) and (44). In this case, the suffix h
and j are attached to clarify that XX, YY, and ZZ depend on the time Th and the j-th
characteristic point out of the first characteristic points. Computation of the Equations
(43) and (44) is performed by substituting values obtained from the Equations (40)
to (42) for XXhj, YYhj, and ZZhj and moreover, substituting a value measured from
the actual photographic image Ph for Uhj and Vhj.
[0184] Obtaining the displacement value (distortion value) (δ XX, δ YY) at every position
(XX, YY, ZZ) through interpolation represents the fact of obtaining the displacement
value (distortion value) at any position under the condition that the displacement
value (distortion value) at (XXhj, YYhj, ZZhj) which is the position of the j-th characteristic
point is (δ XXhj, δ YYhj). In this case, j = 1,..., J. Moreover, the position in the
three-dimensional real space described here represents a coordinate system based on
the video camera at the time Th.
[0185] To perform interpolation, the Delaunay division is first performed in a three-dimensional
real space. That is, division of Voronoi region is performed by assuming J characteristic
points as mother points to perform the Delaunay division having a dual relation with
the division of the Voronoi region. Each Delaunay-divided region forms a convex polygon
using mother points (that is, first characteristic points) as vertexes. Because an
optional point (XX, YY, ZZ) in a three-dimensional real space is included in a Delaunay
convex polygon (Delaunay-divided region), values obtained by weighting and averaging
the displacement values (distortion value) (δ XXhj, δ YYhj) of the vertexes of the
Delaunay convex polygon (first characteristic points in which the displacement values
(distortion values) are already obtained) so as to be inversely proportional to the
distance from the point (XX, YY, ZZ) up to each vertex of the polygon is used as the
displacement value (distortion value) of the point (XX, YY, ZZ). Thus, it is possible
to obtain the displacement value (distortion value) at a position other than J first
characteristic points.
[0186] The Voronoi region and Delaunay division are described in detail in the description
part (p. 1064) of computation geometry of "GENDAI SURIKAGAKU JITEN (transliterated)
(issued by Maruzen Co., Ltd.)."
[0187] Thus, in steps S63 and S64, the displacement value (distortion value) at each of
J first characteristic points is first obtained in accordance with the Equations (40)
to (44) by using the Rh, Sh, Xj, Yj, and Zj obtained in step S61 and the measured
values (Uhk, Vhk). Then, the Delaunay convex polygon is obtained by assuming J characteristic
points as mother points. For each position in each Delaunay convex polygon, the displacement
value (distortion value) is obtained by weighting and averaging the above-obtained
displacement values (distortion values) of vertexes (that is, first characteristic
points).
[0188] In this connection, the displacement value (distortion value) depends on the time
Th and moreover, depends on a position in a three-dimensional real space. That is,
the displacement value (distortion value) is the function of Th and also, the function
of the position (XX, YY, ZZ) in the coordinate system based on the video camera. The
relation of the displacement value (distortion value) between the Th and (XX, YY,
ZZ) is obtained in steps S63 and S64. Steps S63 and S64 are computation steps for
obtaining the displacement value (distortion value) of each point in a three-dimensional
real space at each time.
[0189] It is important for the computation steps for obtaining the displacement value (distortion
value) of each point to obtain the displacement value (distortion value) at an optional
point under the condition that the displacement value (distortion value) at (XXhj,
YYhj, ZZhj) which is the position of the j-th characteristic point is equal to (δ
XXhj, δ YYhj). It is also possible to use other method instead of the Delaunay division
under the above condition.
[0190] In step S62, a position (virtual position based on world coordinates) to which the
building (second object) 91 formed through CG is set is obtained. Moreover, in step
S61, the rotation matrix Rh and parallel displacement vector Sh showing the position
and attitude (direction) of the video camera at each time Th (h = 1,...,H) are obtained.
[0191] Therefore, in step S65, the processing circuit 32 reads world-coordinates-based virtual
positions (Xm, Ym, Zm) of all the points (assumed as M points) constituting the building
(second object) 91 formed through CG from the data memory 3, applies the rotation
matrix Rh and parallel displacement vector Sh also read from the data memory 33 to
the virtual positions, obtains the position (XXhm, YYhm, ZZhm) shown by the coordinate
system based on the video camera at the time Th, and stores the position (XXhm, YYhm,
ZZhm) in the data memory 33. In this case, m = 1,...,M. That is, the following Equations
(61) to (63) are computed.

[0192] Then, in step S66, the processing circuit 32 obtains the displacement value (distortion
value) (δ XXhm, δ YYhm) obtained in steps S63 and S64 and corresponding to the position
(XXhm, YYhm, ZZhm) obtained from the Equations (61) to (63) in accordance with the
following Equations (64) and (65).

[0193] Then, the (δ XXhm, δ YYhm) is added to (XXhm, YYhm, ZZhm). The added position (XXhm
+ δ XXhm, YYhm + δ YYhm, ZZhm) serves as the final position of the m-th point constituting
the building (second object) 91 formed through CG. Of course, the position is the
coordinate system based on the video camera at the time Th.
[0194] Then, the position (UUhm, VVhm) of the projected image of the m-th point constituting
the building(second object) 91 formed through CG is obtained. That is, the following
Equations (66) and (67) are computed.

[0195] The Equations (61) to (63) and the Equations (66) and (67) are computed on every
m = 1,...,M. Thereby, it is possible to compute the projected image of the building
(second object) 91 formed through CG.
[0196] In the case of this embodiment, the displacement value (δ XXhj, δ YYhj) is obtained
in accordance with the Equations (40) to (44) by assuming that a displacement value
is present only in the directions of a two-dimensional plane (X, Y) based on the video
camera. However, it is also possible to assume that a displacement value is present
in Z direction. That is, it is possible to assume the minimum value of (δ XXhj, δ
YYhj, δ ZZhj) meeting the following Equations (68) and (69) as a displacement value.

[0197] However, (XXhj, YYhj, ZZhj) in the above Equations can be obtained from the Equations
(40) to (42). In this case, by obtaining the displacement value of an optional position
under the condition that the displacement value (distortion value) at (XXhj, YYhj,
ZZhj) which is the position of the j-th characteristic point is equal to (δ XXhj,
δ YYhj, δ ZZhj), it is possible to obtain the displacement value at each position.
The position (UUhm, VVhm) of the projected image of the m-th point constituting the
building (second object) 91 formed through CG is shown by the following Equations
(70) and (71) instead of the Equations (66) and (67).

[0198] In the above Equations, (δ XXhm, δ YYhm, δ ZZhm) denotes the displacement value (distortion
value) at the position (XXhm, YYhm, ZZhm) obtained by the Equations (61) to (63).
[0199] Finally, by synthesizing the projected image of the building (second object) 91 formed
through CG with the photographic image Ph, it is possible to obtain a synthesized
image to be finally obtained at the time Th. By performing the above operation for
all times of h = 1,...,H, it is possible to obtain synthesized images from the time
T1 up to the time TH.
[0200] By using the technique of the second embodiment, a displacement value (distortion
value) is added so that the virtual position of an object (second object) to be synthesized
designated by an operator coincides with the position of a characteristic point of
a photographic image actually photographed at the time for each time and each position
in a three-dimensional real space. Therefore, the position of a synthesized image
is not displaced.
[0201] Moreover, it is possible to determine the displacement value (distortion value) at
every position in a three-dimensional space and a displacement value (distortion value)
is added to every portion constituting a second object without distinguishing between
vertexes, sides, planes of an object (second object) to be synthesized. Therefore,
there is no problem on alignment of sides and planes described in the first embodiment.
[0202] Moreover, various modifications and applications can be considered other than the
above description as long as they are not deviated from the gist of the present invention.
Therefore, the gist of the present invention is not restricted to synthesis of a CG
image formed through CG with a plate having characteristic points but the gist includes
every case related to synthesis of a CG image formed through CG with a real image.
[0203] As supply media for supplying a computer program for performing the above processing
to users, it is possible to use not only recording media such as a magnetic disk,
CD-ROM, and solid state memory but also communication media such as a network and
satellite.
[0204] As described above, according to the image synthesizing apparatus of claim 1, the
image synthesizing method of claim 8, and the supply medium of claim 15, a coordinate
transform function is obtained in accordance with a first characteristic point nearby
a synthesis position for synthesizing an object and fourth coordinates on a three-dimensional
coordinate system corresponding to a second image are obtained by applying the coordinate
transform function to third coordinates so as to synthesize the projected image of
the object at a position corresponding to the fourth coordinates of the second image.
Therefore, it is possible that the projected image of the object seem to be natural
in first and second images.
[0205] According to the position detecting apparatus of claim 16, the position detecting
method of claim 17, and the supply medium of claim 18, a coordinate transform function
is obtained in accordance with a first characteristic point nearby an object and fifth
coordinates on a three-dimensional coordinate system corresponding to a second image
are obtained by applying the coordinate transform function to third coordinates so
as to detect the difference between the fourth and fifth coordinates. Therefore, it
is possible to accurately compute the positional relation of a third image in the
first and second images.
[0206] According to the image synthesizing apparatus of claim 19, the image synthesizing
method of claim 21, and the supply medium of claim 23, a position to which the projected
image of a second object is set is corrected in accordance with a distortion value.
Therefore, it is possible to control swinging of a synthesized image.
Industrial Applicability
[0207] An image synthesizing apparatus can be applied to the case of synthesizing a computer-graphics
(CG) image with a real image photographed by a video camera.
DESCRIPTION OF SYMBOLS
[0208]
1 ... Plate, 2 ... Image pickup section, 5, 6 ... Ball, 11 ... Input section, 12 ...
Control section, 13 ... Computing section, 14 ... Image data accumulating section,
15 ... Driving section, 16 ... CG data storing section, 17 ... Display section, 18
... Reproducing section